Decision making is the cognitive process of choosing an action among a set of alternatives. Decision making is often studied in experiments, composed of trials, each associated with a single decision. While a decision in a trial is primarily determined by the relevant features of the alternatives in that trial, biases are commonly observed 1 .Of specific relevance to this work are participant-specific tendencies to prefer one alternative over the other(s). Such biases, which we term idiosyncratic choice biases (ICBs) have been described as early as half a century ago in perceptual discrimination [2][3][4] and operant learning tasks [5][6][7] .In discrimination tasks, the ICBs interfere with the estimate of perceptual noise. In

Idiosyncratic tendency to choose one alternative over others in the absence of an identified reason is a common observation in two-alternative forced-choice experiments. It is tempting to account for it as resulting from the (unknown) participant-specific history and thus treat it as a measurement noise. Here we quantify idiosyncratic choice biases in a perceptual discrimination task and a motor task. We report substantial and significant biases in both cases that cannot be accounted for by the experimental context. Then, we present theoretical evidence that even in idealized experiments, in which the settings are symmetric, idiosyncratic choice bias is expected to emerge from the dynamics of competing neuronal networks. We thus argue that idiosyncratic choice bias reflects the microscopic dynamics of choice and therefore is virtually inevitable in any comparison or decision task.

No abstract

" Additionally, the y-axis label in Fig. 2d should have read "Expected p cw ". The error has been corrected in the print, PDF and HTML versions of this article.